Virtual Assistant for all type of bank.pdf

Introduction
In the modern banking landscape, virtual assistants have become increasingly popular tools for banks to enhance customer service, improve operational efficiency, and drive digital transformation. These virtual assistants, powered by artificial intelligence (AI) and natural language processing (NLP), offer a wide range of functionalities, from basic customer support to personalized financial advice. This article explores the role of virtual assistants in banking, their benefits, challenges, and future prospects.

Role of Virtual Assistants in Banking
Virtual assistants in banking serve as digital concierges, offering customers a convenient way to interact with their bank through voice or text interfaces. They can assist customers with a variety of tasks, such as checking account balances, transferring funds, paying bills, and even providing financial insights and advice. Virtual assistants can also help banks streamline their operations by automating routine tasks, such as answering frequently asked questions and processing simple transactions, freeing up human agents to focus on more complex issues.

Benefits of Virtual Assistants in Banking
Improved Customer Experience: Virtual assistants provide customers with instant, round-the-clock support, enhancing their overall banking experience.

Increased Efficiency: By automating routine tasks, virtual assistants help banks reduce operational costs and improve efficiency.

Personalized Service: Virtual assistants can analyze customer data to offer personalized financial advice and product recommendations.

24/7 Availability: Unlike human agents, virtual assistants are available 24/7, providing customers with access to banking services anytime, anywhere.

Scalability: Virtual assistants can handle multiple customer inquiries simultaneously, allowing banks to scale their customer service operations more effectively.

Data Analytics: Virtual assistants can analyze customer interactions to identify trends and patterns, which banks can use to improve their products and services.

Challenges of Virtual Assistants in Banking
Security Concerns: Virtual assistants may raise security concerns, especially when dealing with sensitive financial information. Banks need to ensure that their virtual assistants comply with strict security standards.

Integration Issues: Integrating virtual assistants with existing banking systems and processes can be challenging and may require significant time and resources.

Accuracy and Reliability: Virtual assistants need to be highly accurate and reliable, especially when providing financial advice or processing transactions.

User Adoption: Some customers may be hesitant to interact with virtual assistants, preferring traditional banking channels.

Regulatory Compliance: Virtual assistants need to comply with various regulations, such as data protection and privacy laws, which can vary across different jurisdictions.Future Prospects of Virtual Assistants in Banking

1. Project Idea Presentation

“Virtual Assistant for all Banks”

Presented By
71806176E – Rushikesh A. Raut.
71806114E – Sarfraj H. Khadim.
71922962G – Mayuri M. Khanvilkar.
71923020K – Suraj S. Hande.

2. Problem Statement
The Banking industry in India is rapidly progressing with increased customer base and due to
newly improved and innovative facilities offered by technology. As the coin has two faces
likewise technology also has its two sides on Indian banking Sector-the positive and the
negative side.

Few banks are ahead of others while many are lying behind for saying advance technology.
This may be due to lack of investment or lack of infrastructure.

So we have to develop a solution which will fill these technology gaps and will introduce
advance technology to all banks.

3. Introduction
Idea is to develop a centralized platform with virtual assistant where customer of any bank can access banking
services and support like monitoring account, fraud prevention, raising issue, etc.

User will be giving command to virtual assistant via interface with either voice or text.

This platform could bring coherence and stimulate the current online banking services and support system.

AI-powered bots will serve customers promptly and efficiently, therefore changing the landscape of customer
service not for only particular bank but to all the banks.

4. Motivation and Objective
The Goal to develop platform where customer can connect virtual assistant and avail any
banking service and support for all banks.

The goal is to automate and stimulate online banking services and supports for all the
bank

Developing A platform where user can manage his/her all bank accounts.

To Reduce the stress on current banking system.

Bringing coherence in all banks working system.

5. What Virtual Assistant can do
Customer Services:
•Opening an account(Saving, Current, Business)
•Make A Deposit (with E₹UPI)
•Take Out A Loan
•Deposit Or Cash A Check
•Apply For A Credit or Debit Card
•Pay Bills
•Many more……
Customer Support :
•General queries and concerns
•Grievance redressal
•Debit or credit card hot listing or blocking
•Loan-related queries and concerns
•Many more…..

6. What we will be offering
•Developing platform with Virtual Assistant for all the services and supports will be a very large scale
project.
•So in order to fit it as a last year project we will be only focusing only on customer support and few
primary services
•Customer Support will have
•General queries and concerns
•Grievance redressal
•Debit or credit card hot listing or blocking
•Loan-related queries and concerns
•Customer Services will have
•Opening an account(Saving, Current, Business)
•Make A Deposit (with E₹UPI)
•Take Out A Loan
•Deposit Or Cash A Check
•Apply For A Credit or Debit Card

7. Virtual Assistance in current Banking System
•chatbots implementation in Indian banks started during 2016 to 2019 and majority of private
banks have implemented these technologies.

•The services of chatbot and virtual assistants are available 24*7 in the 6 banks which have
implemented the services except for Canara Bank.

•In Canara Bank the robots are installed in the bank premises and operate during bank working
hours.

•like HDFC bank and Yes bank have provided an integration of the chatbot with Amazon’s Alexa

•ICICI Bank and Axis Bank has extended the chatbot feature through mobile apps which provides
the customer an option of banking on the go

8. What we will be improving :
Currently service of Virtual assistant is only available for few banks customer. We will be
centralizing the process and making it available to all banks customer.

Grievance redressal time will decrease and grievances will be resolved within less span of
time.

Inter banking communication will become strong.

Reducing Bank’s expenses on technology.

Checking overall operational and financial performance of the banks.

9. Why will banks connect with us
Many banks can’t afford advance technologies like AI, ML, etc. So our platform will be
affordable and convenient way for them to provide quality services to their customer.

Inter banking connection become strong and services based on inter banking
communication will be faster.

It will help banks engage more customers and also will assist in escalating costumer
satisfaction.

It will be a feasible solution for many banks with the limited staff available in their
branches

And also to the people in pandemic situations like covid, etc.

10. Scope of the project
There are more than 120,000 bank branches all over India, if we consider 1 user per 10
branches to our system in one day, then there will be 12,000 users per day,

which will sum to 360,000 users/month and 43,20,000 user per year. This we can
consider as base case.

This system can also be implemented as like extension to UPI which will make it easier to
design and operate.

Implementing all banking services and supports could be a very large scale project.

11. Project work
Since developing a full scale project will be to vast for our last year project, we will bw
developing a small scale project with limited functionalities whose overview can be like,

12. LITERATURE SURVEY :
Sr
No.
Title of the Paper Author Observations
1 Axis Aha! surges with over 10 million
Conversational Engagement
Active.ai (2019) Worked on the huge success of axis
bank chatbot and its causes which we
will be considering in our project.
2 Does the Future of Indian Banking Lie in
Chatbots?
Dash S (2018) works on difficulties to implement
chatbot in India which we need to
overcome.
3 A Review of Chatbots in the Banking
Sector
Shashank Bairy R (2021) Worked on current diversity of
chatbot in Indian banking sector,
which we are going to overcome with
centralization
4 Customers’ Attitude towards Chatbots in
Banking Industry of India
Gupta, A., & Sharma, D.
(2019).
Worked on attitude of customers
towards chatbot and reviews of
customers about pros and cons of
chatbot.

13. FEASIBILITY STUDY
Technical Feasibility
Que - Framework required to be compactible with both
frontend and backend which will make development
easier.
Django is a high-level Python web framework that enables
rapid development of secure and maintainable websites. Built by
experienced developers, Django takes care of much of the hassle of
web development, so you can focus on writing your app without
needing to reinvent the wheel.

Que – how it will handle heavy workload?
We will be developing application in python backend so it
will be easier to deploy the application on docker so that it can
handle heavy workload.
Operational Feasibility
Que – Any such System is currently operating in
India?
Not the same, but many other banks have their own
private Chatbot. We will be Centralizing it so that other banks can
use it as well.



Que – Is the project possible or not?
yes, there are many difficult technical tasks which we
need to handle but technically these project can deployed
successfully.

14. Legal Feasibility
▶Any Banking related software in India
needs an permission from RBI and needs to
follow security and other norms put forth
by RBI.
▶For that we need to provide best application
security we can.
Schedule Feasibility
▶Assuming 100% efforts by all teammates
will surely result into completing the
project on time.
▶The project can be completed in period of
6-8 months.

15. SYSTEM REQUIREMENT
At User’s end “
•Web browser
•Android mobile if in application
Server Side(to run application server)
•8GB RAM
•512 GB Disk space
•Django,
•Python 3.8
•SQL Server
Tools:
•PyCharm
•SQL workbench
•Notepad++
•Browser

16. CHATBOT ARCHITECTURE
Action execution & info.
retrieval
Data sources
User request
Language understanding
/natural language
procedure
Response generation
Chatbot response
Dialogue
management

17. Data Flow Diagram (Level 0)

18. Data Flow Diagram (Level 1)

19. Data Flow Diagram (Level 2)
Customer

20. PROJECT PLAN 1.0 & 2.0

21. UML Diagram : Use Case Diagram

22. Chatbot Connection
Banking Server
UML Diagram :Sequence Diagram

23. UML Diagram: Class Diagram

24. UML Diagram:
State Diagram

25. Implementation:
oTools and Technology used
oTools Used:
oPyCharm
oMySQL Workbench
oVisual Studio Code
oTechnology:
oFlask Framework :-
Flask is a light-weight framework popularly categorized as a micro framework. Flask comes
with some standard functionalities and allows developers to add any number of libraries or plugins for
an extension. If you have a simple, innovative use case to be added to an existing application, Flask
should be your choice as it offers flexibility. Flask comes with a small set of easy to learn API, and the
documentation is excellent. If you are new to Python, start your web development with Flask, so that
you can get the feel of backend and frontend both as well as learn the core concepts well.

26. oNatural language Processing:
Natural language processing gives machine the ability to ingest the given input, break it down, extract it's
meaning , determining appropriate action and answering user in there natural language.
Natural language processing (NLP) has two subsets Natural language understanding (NLU) and natural
language generation (NLG). NLU takes unstructured data as input and convert it into structured data so machine can
understand and act upon it. NLU focuses on extracting the meaning from user input query.
Natural language generation (NLG) simply converts the answer generated by chatbot in structured data to
human understandable natural language.

The five phases of NLP involve lexical (structure) analysis, parsing, semantic analysis, discourse
integration, and pragmatic analysis.
1. Lexical Analysis and Morphological
The first phase of NLP is the Lexical Analysis. This phase scans the source code as a stream of characters and
converts it into meaningful lexemes. It divides the whole text into paragraphs, sentences, and words.
2. Semantic Analysis (Parsing)
Semantic Analysis is used to check grammar, word arrangements, and shows the relationship among the words.
Example: Agra goes to the Poonam
In the real world, Agra goes to the Poonam, does not make any sense, so this sentence is rejected by the Syntactic
analyzer.

27. 3. Semantic Analysis
Semantic analysis is concerned with the meaning representation. It mainly focuses on the literal meaning
of words, phrases, and sentences.
4. Discourse Integration
Discourse Integration depends upon the sentences that proceeds it and also invokes the meaning of the
sentences that follow it.
5. Pragmatic Analysis
Pragmatic is the fifth and last phase of NLP. It helps you to discover the intended effect by applying a set
of rules that characterize cooperative dialogues.

28. TEST CASES AND TEST RESULT
SR.NO Test Cases Test
Result

1 Mobile no: Registered and Length
must be 10 digit in numerical
format only
Run
2 Bank account details : Mobile
number must registered to bank
Not tested
3 OTP: Sms delivery to registered
mobile number within 10 sec
Run

29. SR.NO TEST CASES TEST RESULT
1 Mobile number: Put valid
mobile number
Run
2 OTP: SMS delivery to
mobile number within 10
sec
Run
❖ Test Cases and Test Result for Login
OTP Generation and Validation:

30. OTP Generation and SMS sending
OTP Validation:

31. Dependency Tracking:
- Banking Server : For Development, Testing and modeling purpose.
Status : In progress.

32. Conclusion:
It could be concluded that the portal and Chatbot will be seamless way of
communication in banks during and after Covid-19.


The Virtual Assistant/Chatbot tool along with machine learning and natural language
processing techniques is a complete data set of questions, which is to be implemented
on daily basis at the “May I Help You” desk of banks.

33. REFERENCES
[1] Dash S (2018). Does the Future of Indian Banking Lie in Chatbots? April 11. Retrieved on December
15, 2019 from https://www.entrepreneur.com/article/311795
[2] Maru, P. (2018). HDFC bank launches IRA 2.0 the advance version of its interactive humanoid, April
27. Retrieved on August 11, 2019 from
https://cio.economictimes.indiatimes.com/news/enterprise-services-and-applications/hdfc-bank-launches-i
ra-2-0-the-advance-version-of-its-interactive-humanoid/63936738
[3] Parwatay, S. (2019). Chatbots are the future, April 10. Retrieved on December 15, 2019 from
https://www.axisbank.com/progress-with-us/tech-talk/chatbots-are-the-future
[4] Arati A. Dobariya, Ajaykumar T. Shah, "Banking Inquiry Chat Bot", IJSTE - International Journal of
Science Technology & Engineering | Volume 5 | Issue 7 | January 2019
[5] Thomas, M. P. (2017). Meet Mitra: Canara Bank's new robotic customer care executive. Retrieved on
December 15, 2019 from
https://www.theweek.in/news/sci-tech/mitra-canara-bank-robotic-customer-care-executive.html.